Title :
Adaptive deep-cut method in ellipsoidal optimization for electromagnetic design
Author :
Saldanha, R.R. ; Takahashi, R.H.C. ; Vasconcelos, J.A. ; Ramírez, J.A.
Author_Institution :
Centro de Pesquisa e Desenvolvimento em Engenharia Eletrica, Univ. Federal de Minas Gerais, Belo Horizonte, Brazil
fDate :
5/1/1999 12:00:00 AM
Abstract :
This paper presents an adaptive deep cut algorithm for the ellipsoid method. The formulation proposed employs a variable cut depth which depends on an estimate of the current ellipsoid center distance to the solution. These adaptations in the formulation provide an enhanced convergence in the algorithm without losing robustness. The results of an analytical problem and benchmark problem 22 indicate the applicability of the procedure suggested
Keywords :
convergence of numerical methods; electromagnetic field theory; inverse problems; optimisation; adaptive deep-cut method; benchmark problem 22; current ellipsoid center distance; electromagnetic design; ellipsoidal optimization; enhanced convergence; robustness; variable cut depth; Convergence; Design optimization; Electromagnetic analysis; Electromagnetic fields; Ellipsoids; Inverse problems; Minimization methods; Optimization methods; Robustness; Stochastic processes;
Journal_Title :
Magnetics, IEEE Transactions on
